eCommerce Behavioral Segmentation Examples For 2024

Did you know 87% of all shoppers now begin product searches online before purchasing?

Now, you’ve been in the online marketing game long enough to know that targeting all these shoppers wastes a lot of time and money. 

Without behavioral segmentation, you cannot accurately serve personalized marketing content to potential customers.

In this article, we'll talk about:

Behavioral Segmentation Methodologies

12 Behavioral Segmentation Strategies (with Examples)

Benefits of Behavioural Segmentation

How to Implement Behavioural Segmentation in Your Marketing Strategy

Personalized content is where the real money is made. 

Unlike most guides on behavioral segmentation, here you will find the best strategies for grouping prospects based on their actions. 

What Is Behavioral Segmentation?

Behavioral segmentation is a marketing technique that divides prospects into buckets.

These buckets are based on their interactions with your business.

It focuses on actual prospect behavior. Their actions and engagement. Rather than just demographics. 

Marketing campaigns can be tailored based on behavioral profiles to serve the most relevant content, offers, and messages to specific groups demonstrated by their interaction with your brand or product. 

For example, if a prospect purchases Men’s shoes on your website, you might want to send them marketing emails showing that you also sell shoe polish and socks that compliment their new shoes. 

Why Is Behavioral Segmentation Important?

Why does this matter, you ask? 

Honestly, you know it matters, but your real question is: 

"Why is this important enough for me to devote my time and energy to it?”. 

Well, here is why:

1. Digital Data and Analytics: Technology allows you to collect detailed data on website visits, app usage, and ad interactions that show actual behavior. Advanced analytics translates this data into actionable segments. Predictive AI models can leverage this data to help you make better marketing decisions.
2. Personalized Marketing: Today's customers expect personalized and relevant experiences. Behavioral segmentation makes this level of customization possible.
3. Customer Retention: Acquiring new customers costs more than retaining existing ones. Behavioral segmentation allows you to understand customers better to serve them effectively long-term.
4. Omni-Channel Marketing Complexity: With customers engaging across channels, behavioral data connects disparate actions into clear insights.  

Behavioral data comes from consumer actions. This includes buying history, website activity tracking, survey responses, and other sources.

This data is then analyzed using sophisticated methods to generate segments, insights, and predictions.

Behavioral Segmentation Methodologies

The segmentation process helps you personalize your marketing efforts.

Knowing your prospect's behavior enables you to customize their experience to their specific problem or desire. 

Some types of behavioral segmentation methodologies include

• RFM (Recency, Frequency, Monetary) Analysis: This analyzes customer transaction data to group customers based on the recency of their last purchase, purchase frequency over time, and monetary value across purchase history.
• Product Use Frequency: Segment groups based on usage rates. Usually, light, medium, and heavy product usage. Different engagement strategies are used for different usage levels.
• Customer Journey Mapping: Formulate data categorizations for stages of the typical customer journey from initial awareness to becoming loyal brand advocates. You can serve more relevant content for each customer journey stage based on the data. 
• Micro-segmentation: Creating highly customized, small segments almost at the individual customer level. Based on deep behavioral signals and predictive analytics.
• Omnichannel Segmentation: Creating unified cross-channel behavioral profiles. Considers engagement beyond a single touchpoint but across devices, in-store, website, mobile, etc., in one 360-degree customer view.

Beyond marketing, the segment data informs decisions business-wide.

From supply chain logistics to forecasting staffing for customer service rush hours based on purchase cycles. Behavior doesn’t lie when planning for realities.

12 Behavioral Segmentation Strategies (with Examples)

We get it. 

You’re hungry for advanced behavioral segmentation strategies with money behind them.

Let’s explore the high-impact categories that enable personalized experiences that’ll skyrocket conversions and LTV.

1. Purchasing Behavior

At its core, Purchase Behavior builds customer groups based on frequency, recency, and average order value metrics. But sophisticated models combining behavioral data signals spot things like:

• Consumer Preferences
• Trending Customer Behaviors
• Convenience
• Decision Factors

This segment groups by actual purchase history.  It considers what, when, where, and how much they buy.

For example, you as a retailer may segment “New Customers” (First-Time Buyers). This segment identifies customers who have made their first purchase within the last 30 days. You would prioritize their onboarding experience to give a memorable early impression.

Here are some standard Purchasing Behavior Segments:

New customers:  Those who recently made their first purchase 

Repeat customers:  Those who have made more than one purchase

Multi-product: Multi-category shoppers vs. category shoppers

Upselling: Customers who have exhibited behavior indicating they will buy more expensive offerings.  

2. Big Spender Signals

Spotting potential "Big Spender Signals" early is an advanced behavioral segmentation tactic.

It involves identifying visitors exhibiting patterns that resemble your highest lifetime value customers before they hit whale-sized spending thresholds.

We’re talking about seemingly innocuous behaviors like reading premium content sections, bookmarking high-ticket items, and signing up for stock alerts on luxury goods. 

For example, when someone bookmarks a $2000 designer bag and then browses high-end bracelets afterward − your VIP concierge could reach out: 

"Hi! As a fan of our collections, I wanted to offer you early 24-hour access to our new gemstone lineup before the official launch next month, plus invite you to an exclusive client event showcasing the pieces in person. I look forward to meeting you!"

The right personalized outreach makes it feel organic and accelerates the customer journey. 

Special services, exclusive early access, and VIP treatment drive brand loyalty and word-of-mouth with these MVPs.

3. Technology Adoption

Technology adoption segmentation separates customers based on when they first start purchasing advanced new products you offer. 

For example, in the tech niche, it could be wearables, smart homes, or the latest software. 

The benefits? 

Your marketing messages are tailored to align perfectly with where each group stands adoption-wise. As a result, you make more sales. 

Here are the Technology Adoption Segments:

1. Innovators: First ones embracing cutting-edge products  
2. Early Adopters: Next wave to buy the latest tech/versions 
3. Early Majority: Cautious buyers who wait for some mass adoption
4. Late Majority: Slowest group to adopt new technology

For example, “innovators” who eagerly snatch up barely-tested v1.0 releases to flaunt cutting-edge tech require very little convincing. They want to participate in testing and shaping end-user feedback!  

Meanwhile, mainstream buyers want social proof.

They wait until new releases gain traction and bugs are fixed.

They need content showcasing 5-star peer reviews, retail partnerships, and public buzz to take the plunge.

READ: 35 Brand Examples of Headless Commerce

Your blog comparisons can highlight features that influence hesitant “early majority” groups.

One way of doing this is to use actual purchase history data. Social proof is also effective. Do this by getting a trusted authority or “influencer” to endorse your product. 

4. Micro-Intent Moments

Capturing high-intent "Micro-Moments" with behavioral segmentation offers huge potential for an eCommerce merchant and results in what we call:

Micro-conversions

The concept?

Identifying when a prospect signals peak purchase consideration.

This is determined based on their search terms, clicks, and browsing behavior. 

‍When these actions are triggered, you must respond with hyper-relevant information while interest is red hot.

For example,

The other day, my wife landed on a site after Googling "black cocktail dresses under $100."

She's clearly in an active buying mindset. But black dress options overwhelm her.

Without help, high friction leads her to abandon the session.

… That is until a chatbot pops up with "Hi Lauren! Looking for black cocktail dress ideas under $100? Here are our most popular affordable styles for events." 

And links 3 category sorted dress grids with discounted codes already prepared based on her micro-intent signals.

It was spot on! It knew what she was looking for, and apparently, it could guess the purpose of the purchase.

Beyond searches, traits like reading product reviews, saving items in a cart without purchase, and opening comparison emails can also indicate micro-intents. 

Segments defined by granular signals like this allow you to relieve relevant pain points in real-time across the buyer journey.

5. Customer Loyalty Segmentation

The level of loyalty that a customer has with your brand is measured by “Customer Loyalty”.

Simply put: Loyal customers continually purchase your product or service. 

You can identify this behavior by looking at customers who:

• Make repeat purchases
• Give feedback and reviews 
• Engage with your brand on social media
• Make multiple product purchases 

Based on these data points, you will clearly understand who your most loyal customers are. 

Send a personalized email to your loyal customer segment, thanking them and sharing unique upcoming deals just for them. People love feeling seen and special.

This will make loyal customers feel valued and help retain them. 

Connect more deeply and ask for feedback. The psychology behind customer loyalty is based on building a strong emotional relationship with customers. 

EMOTIONAL, being the underlined word.

Here are some Customer Loyalty Segments:  

1. Champions: Highest brand advocates and loyalty 
2. Loyal Customers: Reliable repeat purchasers
3. At Risk: Decline purchase frequency/risk of switching away
4. Primary Switchers: Actively moving purchases to competitors 

6. Next Purchase Prediction

Next Purchase Prediction is a technique used in predictive analytics to estimate if a customer will make a future purchase.

This prediction is based on a customer's purchase history and behavior. 

This is an extremely powerful strategy. 

But. 

You need lots of customer data to implement it.

If you are a start-up or a small business, using next-purchase prediction won't be that effective as the AI models require large amounts of data to work well.  

The goal is to segment customers based on predicted future purchasing decisions.

Based on the insights, you target customers with personalized product recommendations and promotions for items they're predicted to want next.

This could be in automated emails, SMS messages, or your site. Next purchase prediction helps with improving revenue and customer lifetime value. 

How can you predict the next purchase?

1. Sequence Mining: This involves analyzing a large set of customer purchase history to identify patterns or sequences. For example, if customers frequently buy a computer, followed by a mouse, and then a mouse pad, you might predict that other customers will also want a mouse and mouse pad after purchasing a computer. 
2. Association Rule Learning: Discovers exciting relations between variables in large databases. A standard algorithm used in this method is the Apriori algorithm.
3. Collaborative Filtering:  Automatically predicts what a user is interested in. It can be either user-based (comparing the products that a user has bought so far with other user’s purchases) or item-based (finding associations among the items that the user has bought and other items).
4. Predictive Modeling: Using statistical techniques, it forecasts future behavior. For example, regression analysis could predict a customer's next purchase based on age, income, and previous purchase history.

Recommended reading: 16 Behavioral Targeting Ideas for 2024 (eCommerce)

7. Engagement Level

Engagement level segmentation is another behavioral technique for eCommerce owners.

Engagement Level Segments:  

1. Active advocate: Vocal influencers/ambassadors  (Highly engaged)
2. Engaged sharers: Create user-generated content (Medium engaged customers)
3. Moderate interactors: Occasional posters  (Low-engaged customers)
4. Passive consumers: Just readers/viewers (Disengaged customers)

A tip to leverage this is to track engagement signals like email open/click rates, site time spent, and social follow/shares.

For example, you could:

• Nurture low/medium engaged customers with informative content to re-engage them over time. The content needs to be personalized based on customer behavior. 
• Reward highly engaged existing customers with exclusive perks to maintain their loyalty.
• Reactivate disengaged customers with compelling re-engagement offers.

Do you know Casper? They track mattress trial program completion to identify highly engaged vs. disengaged customers. Disengaged users receive 15% off offers to complete the trial, while engaged users get exclusive new product previews.

Here are some Re-engagement Email Examples

8. Benefit-Sought

Benefit sought = the perceived value they'll get from your services or products.

It divides customers based on the key benefits they seek from a product or service. This is how you optimize your “features” page.

But how do you know what a customer wants? Or what they think your business offers?

1. Talk to them (surveys and customer service)
2. Customer data (based on digital omnichannel interactions with your brand)
3. Let them talk to you (comments, social media engagement, and emails)
4. Monitor sales trends (what products you offer get most talked about)

If gaps exist in your current offerings (based on feedback), develop new products or services to fill them.

Here are some Common benefit sought segments:

Price-Conscious

• Customers who are looking to spend within a specific budget 
• Promote value bundles and sales

Quality-Focused

• Customers who want the highest quality and are willing to pay the price
• Highlight product specs and quality certifications

Style-Oriented

• Customers who want to be unique and set trends
• Showcase new styles and trends

Convenience-Seeking

• Customers who want something convenient that does not consume too much of their time to acquire.
• Offer easy subscription or 1-click options and fast shipping 

9. Purchase Frequency

“How often do they buy?”

Are they Heavy Buyers? Average or Low-Level?

That’s "Purchase Frequency" in a nutshell.

You can use "Purchase Frequency" data to personalize your marketing efforts.  

For example, you still want low-frequency buyers to remember your brand but don't want to bombard them with daily emails.

Here, you can send a weekly email to ensure your brand remains memorable. 

Now, let’s consider frequent buyers. In this case, your marketing efforts will take a different approach. 

Imagine you own an eCommerce clothing brand and see that a group of customers frequently purchases jeans from your store.

You could create a marketing campaign targeted at these customers, offering them a special discount on their next pair of jeans. 

Or, recommend other products that go well with jeans, like stylish tops or accessories. 

This encourages them to make another purchase and shows that you understand their shopping habits.

For the medium and light buyers, you create targeted promotions, such as "Buy 2, Get 1 Free" or "10% off your next purchase" to encourage them to buy more frequently.

Brands like The Dollar Shave Club do this like there is no tomorrow! And it’s worked for them beautifully.

10. Journey Stage

Here are the 5 major eCommerce customer journey stages:

1. Awareness: The customer realizes they need a product in your category
2. Consideration: Starts the research process and considers various products
3. Acquisition: The customer makes the purchase
4. Service: The customer requires assistance post-purchase 
5. Loyalty: The customer becomes loyal or unloyal to your business

Map out the customer journey stages relevant to your business. The way you speak to each group can now be personalized. 

READ: Founder's Guide to Customer Journey Map

For example, here is what your favorite brands do all the time:

For the Awareness stage, they run social media ads showcasing their brand's style and aesthetic, highlighting popular products, and promoting a welcome discount for first-time buyers.

For “Consideration” stage users, they send cart abandonment emails with personalized product recommendations and offer a limited-time discount for customers who complete their purchases.

For people who make their first purchase, they welcome new customers with a post-purchase email sequence that includes product care tips, styling advice, and exclusive promotions for their next purchase.

And finally, they Implement a loyalty program that rewards repeat customers with points, discounts, and early access to new arrivals. This is Retention.

Speaking of retention.

Let’s move on to the next segmentation, Extended Sessions.

11. Extended Sessions

Extended Sessions =  length of time a customer spends interacting with a product or service in a single session.

Cumulative Extended Sessions = total overall customer spend time. (per user).

You can use your custom "Extended Sessions" data to understand which customers are spending more time on your site and what they're doing during that time.

This can help you identify which products or pages are most engaging to your customers.

A special tip for utilizing this would be to analyze customers' behavior during these extended sessions.

Look at the pages they visit, the products they view, and the content they interact with. 

You can even merge this data with other segmentations like user behavior.

For example, suppose customers who spend extended sessions on your site often visit a particular product page.

In that case, you might consider promoting that product more prominently on your site or offering special deals related to that product.

Or, if you find that these customers often read blog posts or other content on your site, consider creating similar content to keep them engaged. 

12. Predictive Churn Scoring

Predictive Churn Scoring is a powerful example of behavioral segmentation that groups customers based on their likelihood to no longer purchase from your store. 

If you own an online supplement store and notice customers who haven't purchased in the past six months.

These customers have a higher risk of churn.

You must catch those last-minute strings that are about to snap. It’s similar to cart abandonment notifications, except this is to retain customers long-term. 

To utilize this insight, you create targeted marketing strategies that resonate with these customers during their sessions.

For example, you might create a "We Miss You" promotion that includes discounts and exclusive offers for customers who haven't purchased in a while.

To automate this, you need to identify and segment the audience first. A successful business is not only about acquiring new customers.

It’s also about keeping them! 

Customer data, such as purchase history, website activity, and customer service interactions, are the most important for this segmentation.

You can collect and process them similarly to the abovementioned process in the other segmentations.

Benefits of Behavioural Segmentation

Personalization

We’re talking hyper-personalization.

‍This means serving customers with relevant content about the problem they are looking to solve.

When you personalize your marketing content based on a consumer’s behavior, you improve conversion rates. 

Budget Allocation 

You’ll know which customers are high-value behavioral groups like repeat purchasers or heavy converts online.

An additional budget can be justified by investing in those segments for the best ROI rather than spreading thinly across groups less likely to respond.

Forecasting

Statistical modeling based on correlations between customer behaviors and outcomes allows you to make reasonably accurate forecasts of churn risk, lifetime value, purchase frequency, etc., to inform budgets.

Targeted Marketing

Zero in on consumers demonstrating tangible interest in products like searching keywords or reading specific content topics. This filters from non-targeted audiences to hot prospects primed for outreach. 

How to Implement Behavioural Segmentation in Your Marketing Strategy

First, analytics 101 - you must understand what your clients are doing. 

How recently, frequently, and heavily are they using/purchasing from you? What pathways through your website or app are popular? This raw data translates into behavioral segments.

Build on these major steps to develop your (or your marketing team’s) own custom behavioral segmentation workflow for Killer Marketing Results:

1. Instrument Everything: Google Analytics, Adobe Analytics, Segment, Heap, and Hotjar … are just some examples. Install plug-ins on your site, embed tracking pixels, and connect analytics and customer data flows across channels. Creating a centralized "conversion command center" to feed behavioral insights. 
2. Reveal Power Segments: Google Audiences, FB Custom Audiences, Klaviyo, Mailchimp Segmentation, you name it. Analyze piles of data to automatically classify shoppers by activities/profiles into groups like promo miners, seasonal splurgers, price-conscious compared to convenience-focused, and many more.
3. Map High-Value Journeys: Dig into the specific step-by-step pathways your VIP segments commonly take from initial awareness > consideration > purchase. Identify exactly what content and features convince them at each stage. 
4. Optimize Pathway Experience: With pathways mapped, enhance site navigation, layouts, and messaging to remove friction/questions for high-value segments as they hit each buying milestone. Dynamic website page layout changes, customer flow revisions, on-site surveys, and chatbot triggers based on behavioral data. 
5. Layer Predictive Intelligence: Machine learning models can ingest behavioral data and then predict which anonymous site visitors resembling past high-converters are most primed for targeting and sales queues. 
6. Automate Omni-Channel Triggers: When a segment demonstrates certain actions like reading specific content or adding certain products to their cart, send automated cross-channel messages using email, notifications, and SMS, messages. 
7. A/B testing of segment-tailored interfaces: Evaluate performance by visitor segment as opposed to overall traffic. Plus/Minus analysis isolates what content, offers, and creative triggers desired behaviors. Refine over time.

CRO360 is a full-service conversion rate optimization platform that offers a comprehensive suite of tools that replace the platforms mentioned above!

By following these steps, your marketing content will be more relevant to consumers. It will speak to exactly where they are now and move them through the customer journey faster.

In conclusion

After exploring the ins and outs of behavioral segmentation, it’s clear - marketing has become personalized, not standardized. 

The brands that blast the same blanket messages en masse to hollow "target" demographics are losing.

‍They fail to resonate emotionally or speak to what different consumers truly care about and respond to.

Behavioral segmentation fixes this through end-to-end personalization powered by data and analytics. 

Bottom line …

Shell out a few bucks for the right tech because it earns itself back 10X over through properly targeted behavioral marketing. Now, put these ideas to work for your business and wow us with the game-changing results!

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